In this paper, we investigate a simple model of behavior, the threshold model (TM) [1]}, [2]}. It consists of \(N\)  individuals arranged in a network. Each individual, described by a state variable \(s_i\)  (\(i=1,\ldots ,N\) ), has either adopted or rejected the behavior in question and has a tendency to switch to adopting (rejecting) if the proportion of individuals in its neighborhood adopting the behavior is greater (less) than its (constant) threshold \(T_i\) . Individuals are chosen at random to be “updated" – i.e., to consider, and possibly change (“flip") their state. We make an analogy with physics by thinking of the individual's state as a `spin' with value \(+1\)  (\(-1\) ) for those who adopt (reject) the behavior.
